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Record W4416666644 · doi:10.1093/jas/skaf409

Dietary zinc-di-tripeptide enhances zinc relative bioavailability and reduces fecal zinc losses compared to zinc sulfate, without compromising performance of growing pigs

2025· article· en· W4416666644 on OpenAlexaff
Pedro Silva Careli, Danyel Bueno Dalto, Rayanne Andrade Nunes, Damares de Castro Fidelis Toledo, Paloma Amorim Vaz, Anne-Cecile Jutten, Raquel Tatiane Pereira, Paulo Levi de Oliveira Carvalho, Gabriel Cipriano Rocha, Jansller Luiz Genova

Bibliographic record

VenueJournal of Animal Science · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsAgriculture and Agri-Food Canada
FundersConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorUniversidade Federal de Viçosa
KeywordsBioavailabilityZincRandomized block designTrace MineralsFactorial experimentTrace mineralFecesNutrient

Abstract

fetched live from OpenAlex

Zinc (Zn) is an essential trace mineral involved in key physiological processes, and organic Zn sources are proposed to have higher bioavailability than inorganic forms. This study aimed to evaluate the bioavailability of a Zn-di-tripeptide (Zn-di-tripep) chelate compared to Zn sulfate (ZnSO4) on growth performance, apparent total tract digestibility of Zn and Zn concentrations in feces, serum, liver, and bone in growing pigs. Ninety male pigs (Landrace × Large White, 63 day-old, 25.44 ± 0.302 kg body weight [BW]) were used in a randomized complete block design based on BW with 10 pigs per treatment over a 60-day period. Pigs were allocated to a 2 × 4 + 1 factorial design, composed by 2 Zn sources (Zn-di-tripep vs. ZnSO4), 4 levels of dietary Zn (30, 60, 90, and 120 mg/kg diet), and a negative control (no supplemental Zn). Digestibility was assessed using acid-insoluble ash as an internal marker, and relative bioavailability was estimated by linear slope-ratio regression. Data were analyzed using Zn source and level as fixed effects, blocks as random effects, and linear and quadratic polynomial contrasts to assess dose-response. Pigs fed Zn-di-tripep or ZnSO4 showed improved performance (P ≤ 0.05) compared to unsupplemented pigs, particularly for average daily gain (ADG) and average daily feed intake (ADFI). From day 0 to 30, pigs fed Zn-di-tripep exhibited a quadratic response (P ≤ 0.05) for ADG and gain-to-feed ratio (G:F), and a linear increase (P ≤ 0.05) in final BW (FBW) and ADFI. From day 30 to 60, both sources promoted linear and quadratic increases (P ≤ 0.05) in FBW, ADG, and G:F, and 120 mg Zn/kg diets resulted in better performance. Fecal Zn concentrations increased linearly (P ≤ 0.05) with dietary Zn level. Pigs fed Zn-di-tripep showed a slight decrease and increase in fecal Zn (P = 0.105) and liver Zn (P = 0.109), respectively, and higher bone Zn concentrations (P ≤ 0.05) than ZnSO4. Serum Zn increased over time (P ≤ 0.05) in all Zn-supplemented pigs, with a trend (P ≤ 0.10) toward higher concentrations in pigs fed Zn-di-tripep than ZnSO4. Apparent total tract digestibility of Zn showed linear effects (P ≤ 0.05), with positive values only for Zn-di-tripep. In conclusion, dietary Zn-di-tripep supplementation improved Zn digestibility, serum and tissue Zn concentrations, and reduced fecal excretion compared to ZnSO4, suggesting greater bioavailability by allowing a reduction in Zn supplementation (∼34%), without affecting pig performance.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.032
GPT teacher head0.286
Teacher spread0.253 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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